1. Field
The following description relates to method and apparatus for high-dimensional data visualization.
2. Description of the Related Art
Analyzing large amounts of data and utilizing such analyzed data is increasingly important for applications processing an overflow of various and plentiful information. Because complex data in various applications are mainly shown as a high-dimensional vector, analytical methods through visualization, including human insight, are becoming more important, along with calculation methods. A dimension reduction technique is a method generally used to visualize high-dimensional data. The dimension reduction technique can convert high-dimensional data into two-dimensional data or three-dimensional data, which can be visible to humans.
However, the dimension reduction technique causes losses and distortion of data. As a result, visualizing high-dimensional data into three-dimensional data has less losses and distortions than visualizing the high-dimensional data to two-dimensional data. Furthermore, visualizing high-dimensional data into two-dimensional data has more advantages than visualizing the high-dimensional data into three-dimensional data due to immediacy of a visualized image and conveniences in interaction.
Despite those advantages and disadvantages of two-dimensional or three-dimensional visualization, the conventional art is limited to visualizing only in one of two-dimensional data or three dimensional data.